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http://dx.doi.org/10.9723/jksiis.2015.20.6.057

Hybrid Approach for Solving Manufacturing Optimization Problems  

Yun, YoungSu (조선대학교 경영학부)
Publication Information
Journal of Korea Society of Industrial Information Systems / v.20, no.6, 2015 , pp. 57-65 More about this Journal
Abstract
Manufacturing optimization problem is to find the optimal solution under satisfying various and complicated constraints with the design variables of nonlinear types. To achieve the objective, this paper proposes a hybrid approach. The proposed hybrid approach is consist of genetic algorithm(GA), cuckoo search(CS) and hill climbing method(HCM). First, the GA is used for global search. Secondly, the CS is adapted to overcome the weakness of GA search. Lastly, the HCM is applied to search precisely the convergence space after the GA and CS search. In experimental comparison, various types of manufacturing optimization problems are used for comparing the efficiency between the proposed hybrid approach and other conventional competing approaches using various measures of performance. The experimental result shows that the proposed hybrid approach outperforms the other conventional competing approaches.
Keywords
Manufacturing optimization problem; Hybrid approach; Genetic algorithm; Cuckoo search; Hill climbing method;
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Times Cited By KSCI : 1  (Citation Analysis)
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